Trusting What You Know: Information, Knowledge,
and Confidence in Social Security
Fay Lomax Cook Northwestern University
Lawrence R. Jacobs University of Minnesota
Dukhong Kim Florida Atlantic University
Can public trust in government be increased by expanding knowledge of the activities government already
performs? This study takes advantage of a naturally occurring experiment—the distribution of personal statements
by the Social Security Administration— to examine the impact of increased domain-specific information on the
public’s knowledge and confidence. Analysis of a large Gallup survey of attitudes toward Social Security finds that
recipients of personal Social Security Statements gained more knowledge of, and confidence in, Social Security than
nonrecipients after controlling for individual differences. These results suggest that citizens’ evaluations of
government institutions echo, in part, the quality and quantity of information distributed to them. The implication
for future research on political trust and confidence is to confirm the importance of expanding analysis from global
to specific objects of evaluation.
T
rust in government is often identified as essential for citizen compliance to the basic
political order (Barber 1983; Miller 1974a,
1974b), generating support for political leaders to
expand taxation, spending, and authority (Chanley,
Rudolph, and Rahn 2000; Hetherington and Nugent
1998), encouraging political participation (Abramson
1983, 195) and social trust (Brehm and Rahn 1997),
and creating approval for the president and Congress
(Citrin 1974; Hetherington 1998) and for incumbent
candidates and government officials (Hetherington
1999). Political trust in the United States remains at
lower levels than in the 1960s,1 and a cottage industry
has developed to restore the public’s trust (e.g., Nye,
Zelikow, and KingNorris 1999; Nye, Zelikow, and
King 1997) through efforts designed to improve the
operation and performance of specific government
institutions and programs and to reduce waste and
corruption (Chanley, Rudolph, and Rahn 2000;
Hetherington 1998).
Some observers have questioned, however,
whether improving government performance can
reverse distrust of government. Surveys have shown
that fluctuations in political trust do not vary across
government institutions with quite different performance records (Bok 1997; McClosky and Zaller
1984; Orren 1997), leading observers to conclude that
public trust and government performance are not
closely related (McAllister 1999). Instead, they attribute the sharp drop in political trust and the fluctuations within this trend both to enduring perceptions
of a threatening and wasteful government and to
media attention to a limited set of notable scandals
and failures such as the Vietnam War and Watergate
whose effects were generalized to ‘‘government in
Washington’’ rather than to specific agencies or
programs (Orren 1997, 87–99).
Recent discussions of the causes of political
distrust have reflected well-known and longstanding
critiques of citizen competence (e.g., Campbell et al.
1960; Schumpeter 1950). In Why People Don’t Trust
Government, Derek Bok suggests that government is
not ‘‘doing a bad job’’ but that ‘‘many people are in
error about the facts’’ and are not ‘‘well enough informed to make reliable judgments about the government’s performance’’ (1997, 56). Others point to the
1
Although Americans’ trust in government soared after the September 11, 2001, terrorists’ attacks on the World Trade Center in
New York City and the Pentagon in Washington, D.C., it had lost half the gain by January 21–24, 2002, according to a CBS/New York Times
poll (Langer 2002). Our description of the public’s low regard for government performance as ‘‘political distrust’’ follows the practice by
many scholars. We later modify this description and define the problem in terms of citizen confidence in institutional performance.
The Journal of Politics, Vol. 72, No. 2, April 2010, Pp. 397–412
Ó Southern Political Science Association, 2010
doi:10.1017/S0022381610000034
ISSN 0022-3816
397
398
fay lomax cook, lawrence r. jacobs and dukhong kim
‘‘stunning disparity between actual and perceived
performance’’ (Orren 1997, 90), to Americans’ tendency
to be ‘‘very critical of government [activities] . . . [that]
they are not very knowledgeable about’’ (Blendon et
al. 1997, 215), and to the ‘‘contradiction between
subjective opinion and objective performance’’ (Nye
and Zelikow 1997, 257). The common theme is that
political distrust results not from weak government
performance but from weak citizen performance in
acquiring accurate information and competently
processing it. The implicit assumption is that a better
informed public would be more trusting of
government.
This critique of citizen competence raises a fundamental question: can increased information about
government performance boost citizen knowledge
and increase trust? Of course, increased information
could back-fire and expose the limitations of government, thus decreasing political trust. Indeed, some
research already suggests that more knowledge feeds
higher expectations and eventually greater disappointment with how Congress makes policy (e.g.
Hibbing and Theiss-Morse 1995, 2002; Kimball and
Patterson 1997).2 Still other research finds no relationship between political knowledge and trust (Delli
Carpini and Keeter 1996, 144–45).
Critiques of the public’s competence to evaluate
government raise several important issues. First,
while research has shown that variations in political
information and knowledge explain much of the
heterogeneity in political attitudes and participation
(Delli Carpini and Keeter 1996; Zaller 1992), there
has been little or no empirical examination of the
impact of information and knowledge on political
trust. Does factual information from expert sources
about the performance of specific government institutions and programs increase, decrease, or have no
influence on the public’s knowledge of and confidence
in them? Second, the acquisition and processing of
information is costly, and, yet, we know little about the
conditions under which information might be used
and affect political trust. What individual traits affect
the propensity of individuals to use new information
and alter their knowledge and trust levels?
In investigating these questions, we depart from
the common research design by studying the public’s
evaluation of a specific government institution and of
a single program. Our approach avoids the past
2
The research by Hibbing and Theiss-Morse (2002) and others
use a general political knowledge index rather than knowledge
about the specific institution that the public is evaluating. In this
paper we examine the impact on confidence of institutionspecific knowledge.
tendency to focus on global evaluations of ‘‘the
government,’’ which relied on the American National
Election Studies (ANES) series on ‘‘trust [in] the
government in Washington’’ (emphasis added; Citrin
1974; Miller 1974; but cf. Levi and Stoker, 2000, 491–
99). This global definition of the object of judgment
(‘‘the government’’) is prone to obscure distinctions
among different government programs and institutions engaged in their own unique activities, outputs,
and relations with clients (Delli Carpini and Keeter
1996; Gilens 2001).
There is some unsystematic evidence of a link
between the public’s evaluation of, and confidence in,
specific government units when detailed information
about the performance of those bodies is presented to
the public, such as with the Department of Energy’s
handling of hazardous waste facilities and nuclear
energy plants (Flynn et al. 1992; Goldsteen, Goldsteen,
and Schorr 1992; Shapiro 1987). Yet we need more
systematic evidence about how domain-specific evaluations of government performance are related to the
public’s confidence in specific government institutions and programs.
We address these questions by examining the
Social Security Administration’s (SSA) mailing to all
eligible Americans of a personal Statement detailing
their past contributions and projected future benefits.
The impact of these mailings is estimated using data
from a Gallup survey of 4,020 adults that was
conducted from November 1999 to January 2000
while the statements were being mailed out. Social
Security offers a testing ground for studying domainspecific information and its effects on knowledge and
public confidence. A sustained body of survey data
on Americans’ ‘‘confiden[ce] . . . in the future of the
Social Security system’’ (e.g., Cook and Jacobs 2002;
Cook, Barabas, and Page 2002) makes it possible to
move from overly general judgments of ‘‘the government’’ toward studying the public’s evaluations of a
particular government program and use of institutionspecific criteria of evaluation— namely, the reliability
of SSA to pay benefits.
The next section discusses existing research on
political information, knowledge, and confidence in
order to specify a set of theoretical expectations. The
second section lays out our research plan based on
the unique confluence of SSA’s mailings and the
Gallup survey. The third and fourth sections analyze
our findings that SSA’s distribution of domain-specific
information improved knowledge and confidence in
Social Security after controlling for individual differences in motivation, cognitive capacity, and social
location.
trusting what you know
An Integrated Framework of
Information and Individual Traits
on Knowledge and Confidence
Explaining the connection of information to the
public’s knowledge and confidence requires an integrated framework that accounts for both differences
across individuals in their dispositions and skills and
the extent to which factually relevant information is
communicated to them (Chong 2000). Three personal traits can affect learning about government
institutions. First, individuals differ in their motivation to invest the necessary time and effort to
processing information, expanding their knowledge,
and incorporating this into their evaluations of
government institutions. Motivation is higher when
a government issue is personally important to an
individual (Campbell 2003; Craig 1996). In the Social
Security context, this means individuals living with a
current recipient or approaching retirement age are
prone to perceive the program as offering a tangible
benefit, which may increase their confidence both
directly by demonstrating its concrete benefits and
indirectly by prodding them to learn about it.
Second, individuals differ in their cognitive capacity to understand new information. A longer
formal education equips individuals with a storehouse of basic facts and instills in them cognitive
skills and strategies for efficiently incorporating new
information (Nadeau, Niemi, and Amato 1995; Nie,
Junn, and Stehlik-Barry 1996).
Third, social location creates differential opportunities for individuals to acquire information and
develop confidence in government institutions. Males
and higher income individuals usually know more
about politics and policy (Bennett 1995; Nadeau,
Niemi, and Amato 1995; Verba, Burns, and Schlozman 1997); women may have less confidence in
Social Security owing to their greater dependence
on it and therefore sensitivity to criticisms of the
program and its exclusion of care-giving years from
calculations of benefits (Dunn 1999; President’s
Commission to Strengthen Social Security 2001).
Race may also play a role owing to past experiences
with government, but it is difficult to predict the
direction of such impact. The federal government’s
promotion of civil rights and the full inclusion
of farm workers and domestic workers in the 1955
Social Security Amendments may generate stronger
confidence among African Americans than whites;
but the opposite could also result from the belated
inclusion of African Americans into Social Security
399
and concerns about lower payouts to African Americans
due to their shorter lifespans on average (Blendon et al.
1997, 207–08; Cook and Barrett 1992; King 1997;
Lieberman 1998).
Independent of individual traits, decisions to collect
and process information and to judge government
institutions might also be affected by the information
government officials and political actors distribute. In
the best case scenario, information that is factual and
detailed in cataloguing regulatory protections and
benefits should improve knowledge and confidence in
government institutions. For example, the four compact pages of the Social Security Statement provide
clear, factual, nonpartisan, and personally relevant
information about Social Security rather than warnings
of imminent collapse or glowing reports about successes. The first and last pages describe without jargon
the operations of the program including its benefits,
financing, and future; the front page assures readers
that the program ‘‘will . . . be there when you retire’’
based on its solid financing for the next four decades,
though the Statement also acknowledge that ‘‘[w]e’ll
need to resolve long-range financial issues.’’ The middle
two pages estimate the individual’s own benefits,
disability payment, and survivors insurance and provide
a full record of the individual’s earnings and contributions to Social Security. This part of the Statement
presents tangible assets in a form familiar to Americans
with a savings account or a traditional annuity plan.
There are two possible alternatives to accounts
that link information to increased trust (Bok 1997;
Gordon and Segura 1997; Kahn and Kenney 1997;
Orren 1997). In the one, individuals with higher
levels of education and income develop lower levels
of confidence because they interpret information as
raising questions about SSA’s promise that benefits
will ‘‘be there when you retire’’ or as demonstrating
that the program is a ‘‘bad deal’’ for them owing to
their relatively higher taxes and relatively lower
benefit levels (Jacobs and Shapiro 1998). According
to a second alternative account, information that is
contradictory may have offsetting effects that blunt its
influence on trust. For instance, reassuring statements
from SSA that benefits will ‘‘be there when you retire’’
may be offset by sober warnings that there is a ‘‘need
to resolve long-range financial issues’’ (Abramson
1983, 232; Delli Carpini and Keeter 1996).
While each of these alternative accounts is
possible, we hypothesize that the Social Security
Administration’s dissemination of information will
enhance citizens’ knowledge of Social Security and
boost their confidence in the program. But we are
not prepared to hypothesize about whether the
400
fay lomax cook, lawrence r. jacobs and dukhong kim
information will affect all citizens in similar ways or
whether it will have differential impacts on those with
more education, income, and motivation. We will
explore these subgroup relationships in detail.
Data and Methods
On October 1, 1999, SSA began mailing annual
Statements of Social Security benefits to all eligible
Americans three months before their birthdays. The
Statement had just started to be mailed out as Gallup
went into the field in November 1999; the result was
that only a fraction of respondents had received a
Statement by survey time. The joint timing of SSA’s
Gallup survey and its mailing of personal Statements
creates a natural experiment that allows us to analyze
the impact of the Statement by comparing those who
were mailed it before the survey against those who
were mailed it after the survey. The analysis is
restricted to people between 25 and 65 (N 5 2,458)
because they alone were eligible for the Statement.3
Measurement
Following the broad tradition of survey research on
institutional confidence (such as the separate
branches of government), Gallup asked: ‘‘How confident are you that Social Security retirement benefits
will be there for you when you retire? Not confident at
all, only a little confident, somewhat confident, or very
confident?’’ The measure is coded 1 to 4. Our knowledge measure combines 16 separate items regarding
Social Security’s benefits, taxation, and administration
and is limited to questions specifically discussed in the
personal Statement distributed by SSA in 1999–2000.
All the knowledge items concern Social Security, and
they vary in difficulty, discrimination, and response
categories in order to minimize acquiescence bias (Delli
Carpini and Keeter 1996; Zaller 1992, 337). Four common question formats were used (Bennett 1995; Converse 1964; Gordon and Segura 1997; Zaller 1992). Five
asked respondents whether they agreed or disagreed
with a factual statement such as whether Social Security
provides benefits to retirees or families of workers who
die. The second format involved four items that posed
a forced choice between two alternatives (e.g., whether
the youngest age one can retire and collect full Social
3
The total N for the survey is 4020; it declined to 2,458
respondents after excluding current recipients of Social Security
or individuals less than 25 years of age or greater than 65 years of
age. The number of respondents declined further to 1855 for
model 1 and 1814 for model 2 after excluding respondents who
refused to answer particular questions (e.g., income).
Security retirement benefits is fixed or will rise in the
future). The third format included two true or false
items about the rising percentage of older Americans
and the relationship between Americans living longer
and long-term Social Security financial projections.
The fourth format involved five open-ended questions
on such topics as the types of benefits that Social
Security pays for and the youngest age someone can
retire today and start receiving full Social Security
benefits. We use all 16 items to construct the latent
knowledge variable. Only 26 respondents, about 1%,
answered all 16 items correctly; 17% scored 13 or
higher; and only one respondent missed all 16 items.
The mean score was 10.19, with a standard deviation of
2.55. Thus, most respondents knew a fair amount
about Social Security, as shown in previous research
(Delli Carpini and Keeter 1996; Jacobs and Shapiro
1998).
The Gallup survey also provides measures of two
sets of potential influences on Social Security knowledge and confidence— whether SSA’s personal Statement had been received and items about individual
motivation, cognitive ability, and social location.
Individual motivation is measured by whether any
household member received Social Security or
whether the respondent was over age 55 (but not
receiving Social Security benefits).4 Together, these
accounted for 20% of the sample and generated a
score ranging from 0 to 2. The highest level of
completed education was the indicator of cognitive
capacity; respondents’ open-ended answers to the
education query were coded into five categories, with
higher scores representing advanced degrees. Advantaged social location was measured by classifying total
annual household income into six categories, with 1
designating less than $20,000 and 6 signifying $100,000
or more. We used dichotomous codes for gender
(male was coded 1) and race (white was coded 1).5
The personal Social Security Statement is measured as ‘‘Statement Mailed’’ and ‘‘Statement Received.’’ The former is measured as the birth month
of respondents. Respondents born in January and
February (16% of the sample) were mailed the
Statements before the survey took place, while respondents born from April 1 through December 31
were not. (Respondents born in March were omitted
because they fell within the month when the survey
4
In the gerontological literature on retirement, age 55 is generally
considered the beginning point at which many individuals begin
to seriously consider retirement and to be more aware of the age
at which they will be eligible for benefits.
5
See the appendix for a fuller description of the variables.
trusting what you know
was in the field.) One (1) represents respondents to
whom the Statement was mailed and 0 those to
whom it should not have been mailed. We assume
that birth months are randomly distributed across the
population of entitled Americans, and therefore there
should be no systematic relation between this variable
and other social location variables.
‘‘Statement Received’’ assesses whether respondents reported receiving a personal Social Security
statement when asked: ‘‘Have you received a written
Statement (Social Security Statement) from the Social
Security Administration in the last year that shows
how much you have contributed to Social Security,
and how much you can expect to receive in benefits?’’
This was scored dichotomously, with 1 representing
receipt. The 27% who reported receiving the Statements is more than would be expected from their
birth month alone (16%). Some of those who
reported receiving a Statement may have requested
one before SSA mailed them; others may have read a
Statement sent to their partner or an acquaintance
(rather than their own).6
We use both measures for the distribution of the
Social Security Statement to examine two distinct
analytic ‘‘treatments’’ (Shadish, Cook, and Campbell
2002). Model 1 uses the ‘‘Statement Mailed’’ measure
to analyze the ‘‘Intent to Treat’’ (i.e., the impact of
the initial condition, the mailed Statement). Model 2
uses the ‘‘Statement Receipt’’ measure (along with
the ‘‘Statement Mailed’’ measure) to estimate the
‘‘Treatment on Treated’’ impact; this examined the
effect on those who reported receiving the mailing.
6
Similar to the fact that some respondents reported receiving a
Social Security Statement who should not have been mailed one
based on the birth month mailing method, a small percentage of
respondents who said they had not received a Social Security
Statement should have received a Statement based on the SSA’s
birth month of distributing the Statements (7%). These may be
citizens who move frequently or threw the Statement away, thinking
it was junk mail, or simply forgot getting it. If the study design had
been an experiment in the laboratory with perfectly controlled
random assignment to the experimental and control groups, no
study participant would have reported not getting a Statement if the
experiment assigned them one. However, this study took advantage
of what was basically a naturally occurring experiment in the field
owing to distribution of SSA’s Statements, and therefore some
slippage occurred. There is no easy way to correct for these
discrepancies with the statistical model, because they are measurement errors inherent to natural experiments. The empirical evidence
reveals that those who are more educated, better off, and more
motivated are more likely to say they received the statement. As a
way to control for this potential source of error in the ‘‘statement
received’’ measure, we estimate the second model including both
variables and the interaction terms. We acknowledge that this model
specification is not a fundamental solution for the measurement
error, but at least we can trace the sources of it and control for it in
the model.
401
Including both measures in the same analysis allows
us to assess the effects of both the government
agency’s effort to disseminate the information and
the effects of actually receiving (or remembering) it.
By incorporating the two measures in Model 2, we
can fully explore the theoretical paths through which
the government’s effort influences citizens’ knowledge
and confidence and the ways that individuals’ social
demographic backgrounds, motivations, and cognitive
skills interact with the government’s effort. In particular, we expect that ‘‘Statement Mailed’’ will influence
‘‘Statement Received,’’ that ‘‘Statement Received’’ will
improve knowledge of Social Security, and that this
enhanced knowledge will in turn increase confidence in
Social Security. These paths are consistent with our
expectation that SSA’s effort to disseminate information contributes to improvement in citizens’ knowledge
of Social Security and subsequently increased confidence in Social Security. In addition, we will examine
the extent to which individual differences in socioeconomic status, motivation, and education level will
moderate the influence of information in building
knowledge about government and trust in its future
performance.
We use structural equation modeling (SEM) and,
specifically, LISREL, to specify and test a path model of
the direct and indirect influences from mailing out the
Social Security Statements to increased confidence in
Social Security (Bollen 1989; Byrne 1998; Pedhazur
1982). Ordinary least square (OLS) estimation can
provide an incomplete and even biased picture of
complex interdependencies, making SEM better suited
to our main purpose of examining how ‘‘Statement
Mailed,’’ ‘‘Statement Received,’’ and ‘‘Knowledge’’ are
causally related to each other and to Confidence in the
future of Social Security.7 We use LISREL and a
Weighted Least Squares (WLS) estimation method
because our data are a mixture of continuous and
ordinal variables.8 In a second set of analyses, we use
7
One of the benefits of SEM models is that we can take into account
the correlated error in survey items. As Green (1988) points out,
correlated error will occur when questions share the same format
and response options and when the placement of questions in a
survey instrument is close to each other. Although different types of
survey items were used in the Gallup survey, there is still a possibility
that correlated error could arise. To correct for correlated response
error, the covariance among the error terms for the correlated items
was freed. See footnote 9 for the details of the operationalization of
the covariance among the items for the latent variable ‘‘Knowledge.’’
8
Because we have ordinal categorical variables, we use polychoric
correlation matrix for input and weighted least squares (WLS)
estimation. Using WLS estimation and polychoric matrix is
appropriate given the noncontinuous nature of our variables
and the nonnormal distributions of some of variables (Joreskog
and Sorbom 1996).
402
fay lomax cook, lawrence r. jacobs and dukhong kim
Maximum Likelihood estimation to test for interactions and potential bias in using WLS (Aiken and West
1991; Joreskog and Yang 1996).
Our analyses proceed in two parts. The first
investigates how the direct measure of SSA’s information distribution (‘‘Statement Mailed’’) relates to
Knowledge and Confidence in Social Security. The
second uses both ‘‘Statement Mailed’’ and SSA’s
information distribution (‘‘Statement Received’’)
where the selection process into ‘‘Statement Received’’ is not perfectly known and thereby potentially open to selection bias. In each section, we test
the effects of information against the potent influences of individual traits.
The Effects of Mailing Personal
Social Security Statements
Table 1 and Figure 1 present the LISREL analysis
results;9 the fit of the data to the hypothesized models
are generally good based on multiple indicators.10 We
estimate the model assuming that all the causal
relationships are recursive— i.e., the causal direction
from the independent to the dependent variables is
one way. Table 1 presents both standardized and
unstandardized coefficients for the direct effects of
9
We treat the variables Income, Race, Gender, Education, Personal Importance, Statement Mailed, and Statement Received as
observed variables. Thus, there is no need to make assumptions
about measurement error. For the latent variable – Confidence –
we assumed no measurement error (i.e. the measurement error
was set to zero) and used a single indicator. For the latent variable
‘‘knowledge,’’ we used 16 items to construct the variable. In this
variable, the measurement error was taken into account by
allowing co-variation between items. To achieve this we freed
some elements of the measurement error matrix (i.e., thetaepsilon matrix). In deciding which items would be freed, we
examined the modification indices for the theta-epsilon matrix.
If the modification indexes are greater than 10, we freed the
covariance for the items. We acknowledge that this rule of thumb
is a rough way to deal with the measurement errors, but it is
better than assuming no measurement errors with a number of
knowledge items; past research (e.g., Gilens 1995; Green 1988)
has shown that measurement error needs to be taken into
account. In model 1 we freed 29 covariance matrixes and 27 in
model 2.
10
For Model 1, the Standardized Root mean Square Residual
(SRMR) is .075, which is smaller than the cutoff of .08, and the
Root Mean Square Error of Approximation (RMSEA) is 0.034,
which is smaller than the cutoff of .06 (Bentler and Dudgeon
1996; Hu and Bentler 1999). Similarly, for Model 2, we have .056
for SRMR and .017 for RMSEA, and they are below the cut
points. These criteria of goodness of fit provide support that our
model is a reasonable reflection of the observed dat. The fit
indexes for Model 2 which does not include the interaction terms
(SRMR 5 .075 RMSEA 5 .034) show a poorer fit than the current model.
individual-level variables on knowledge and confidence, the indirect effects of individual-level variables
on confidence through knowledge, and the total
effect of both the direct and indirect effects.11 For
simplicity of presentation, Figure 1 displays only
standardized coefficients for the statistically significant paths although as noted we estimated all paths
from the individual level variables to ‘‘Statement
Mailed,’’ to knowledge, and to confidence and they
are shown in Table 1.
Relationship between Statement Mailed
and Individual Traits.
We begin our analysis by using the most stringent
measure of SSA’s distribution of information in
Model 1—the mailing of Statements to individuals
with January or February birth months as compared
to those who were mailed later. The first step
examines how ‘‘Statement Mailed’’ is related to social
location (i.e., income, race, gender), cognitive capacity (i.e., education), and motivation (the personal
importance of Social Security due to age and receipt
of benefits). As expected, the coefficients are small
and not statistically significant, supporting the expectation that ‘‘Statement Mailed’’ is a product of
date of birth and not systematically related to
income, race, gender, education, and motivation.12
Impact of Individual Traits on Knowledge .
Table 1 (‘‘Direct Effects’’ Panel, Column 1) and
Figure 1 show that all the variables measuring individual traits have significant direct influences on Knowledge. Better educated individuals know more about
Social Security (b 5 .27), as do individuals with
higher incomes (b 5 .18), men rather than women
(b 5 .07), whites more than nonwhites (b 5 .27) and
those who have a stake in Social Security because
they are approaching retirement or living with a
Social Security recipient (b 5 .24). These results are
11
We also estimated alternative models, which excluded insignificant paths. Those results are not shown here but produced almost
the same findings. This applies to the estimation of Model 2.
12
We used commonly adopted rules to test whether our models
satisfy the ‘‘necessary condition’’ for identification. According to
Bollen (1988, 328), t-rule is a principle way to test the necessary
condition. If the number of free and unconstrained parameters is
smaller than 1/2(p+q)(p+q+1), the model is necessarily identified. The p and q are the numbers of observed variables for X
variables and Y variables. In our model 1, there are 5 X variables
and 18 Y variables. At the same time, we have 73 parameters to
estimate with the information. Model 1 satisfies the t-rule since
73 is less than 276 (1/2*23*24). According to the same logic,
model 2 satisfies the t-rule since there are 103 free parameters and
6 X variables and 21 Y variables.
trusting what you know
T ABLE 1
403
Direct, Indirect and Total Effects of the Variables for Model 1
Independent
variables
Direct effects
A. Social Location
Income
Race (white51, nonwhite50)
Gender (male51, female50)
B. Cognitive Capacity
Education
C. Motivation
Personal importance
D. Information distribution
Statement Mailed
E. Information
Knowledge
Indirect effects
A. Social Location
Income
Race (white51, nonwhite50)
Gender (male51, female50)
B. Cognitive Capacity
Education
C. Motivation
Personal importance
D. Information distribution
Statement Mailed
Total effects
A. Social Location
Income
Race (white51, nonwhite50)
Gender (male51, female50)
B. Cognitive Capacity
Education
C. Motivation
Personal importance
D. Information distribution
Statement Mailed
E. Information
Knowledge
Statement
Mailed
Knowledge
Confidence
b (std. err)
b
b (std. err)
b
b (std. err)
b
.06 (.04)
2.10 (.05)
2.04 (.04)
.06
2.10
2.04
.17 (.03)***
.26 (.03)***
.06 (.03)**
.18
.27
.07
.04 (.03)
2.12 (.04)**
.13 (.03)***
.04
2.12
.13
2.02 (.04)
2.02
.26 (.02)***
.27
2.02 (.03)
2.08 (.05)
2.08
23 (.03)***
.24
.40 (.03)***
.40
—
.05 (.03)
.05
.09 (.03)**
.09
—
—
.27 (.03)***
.26
—
—
—
.00 (.00)
.00 (.00)
.00 (.00)
.00
2.01
.00
.05 (.01)***
.06 (.01)***
.01 (.01)
.05
.06
.01
—
.00 (.00)
.00
.07 (.01)***
.07
—
.00 (.00)
.00
.05 (.01)***
.05
—
—
.01 (.01)
.01
.02
.06 (.04)
2.10 (.05)
2.04 (.04)
.06
2.10
2.04
.17 (.03)***
.25 (.03)***
.06 (.03)*
.17
.25
.06
.09 (.03)***
2.06 (.04)
.14 (.03)***
.09
2.06
.14
2.02 (.04)
2.02
.26 (.02)***
.26
.09 (.03)***
.09
2.08 (.05)
2.08
.22 (.03)***
.22
.45 (.03)***
.45
—
.05 (.03)
.05
.10 (.04)**
.10
—
—
.27 (.03)***
.27
***: p , 5.001 **: p , 5 .01 *: p , 5 .05
The unstandardized (b) and standardized (b) coefficients are presented. The estimation has been conducted by using LISREL 8.5
df 5 203; Chi-Square 5 634.63; AGFI 5 .98; SRMR 5 .075; RMSEA 5 .034
consistent with previous research and our expectations: individuals who are better skilled, more
motivated, and enjoy privileged social positions learn
more about programs and politics (Delli Carpini and
Keeter 1996).
Impact of Individual Traits on Confidence. In
terms of the direct effects of individual traits on Confidence (‘‘Direct Effects’’ Panel, Column 2), personal
importance has the strongest influence (b 5 .40).
Individuals who witness a family member receiving
tangible benefits or are about to receive benefits
themselves are more likely to believe that program
benefits will also exist for them in the future. As
anticipated, men are more likely to have confidence
than women (b 5 .13), perhaps reflecting women’s
trepidation about Social Security’s dependability and
fairness. Education is not directly linked to Confidence, corroborating Abramson’s (1983) warning
404
fay lomax cook, lawrence r. jacobs and dukhong kim
F IGURE 1 The Impact of Mailing the Social Security Statement on Knowledge and Confidence
against presuming an ‘‘education-enhancement’’ effect. While individuals with high cognitive capacity
may be better equipped than others to improve their
knowledge, this does not necessarily lead to greater
confidence in institutional performance. Education
only has an influence indirectly, by equipping individuals to improve their Knowledge of Social Security
(b 5 .07) (‘‘Indirect Effects’’ Panel, Column 3). In a
similar way, income leads to higher Confidence not
directly but rather through expanding Knowledge
(b 5 .05).
In a finding that may help to resolve a current
puzzle, race is related to confidence, with nonwhites
being more confident than whites (b 5 2.12). This
may reflect Social Security’s inclusive racial history
(see Lieberman 1998).
The Impact of Mailing Social Security
Statements on Confidence
The second set of substantive findings offers support
for our core argument: straight-forward, factual, and
personally relevant information increases confidence
in specific government programs once a broad array
of individual traits are controlled. Table 1 and Figure 1
show that SSA’s mailing of Statements had a direct
effect on Confidence in the future of Social Security
(b 5 .09 [Table 1, ‘‘Direct Effects’’ Panel, Column 3]).
However, it does not have a statistically significant
impact on Knowledge.
Consistent with the arguments of Bok, Orren, and
other proponents of the information-enhancement
account, knowledge has a significant effect on Confidence (b 5 .26 [Table 1, ‘‘Direct Effect’’ Panel,
Column 3]): the more people know about Social
Security taxes, benefits, and operations, the more
confident they are about the program’s future. Of
particular importance is that Table 1 shows that the
total impact of ‘‘Statement Mailed’’ on Confidence is
.10 (p , .01) (‘‘Total Effects’’ Panel, Column 3). In
other words, use of the stringent ‘‘Statement Mailed’’
independent variable leads to a modest increase in
confidence in Social Security. Simply mailing information about the program enhances confidence in it
even among individuals with different individual traits.
The Effects of Government Mailing
and Public Recollection of Statement
Receipt
Model 2 includes ‘‘Statement Received’’ and ‘‘Statement Mailed’’ in the same model in order to
trusting what you know
investigate the independent effect of actually receiving the Statement and whether and how SSA’s effort
of sending the statement affects citizens’ knowledge
and confidence. It also examines the statistical interaction of individual traits and Statement Received on
Knowledge and Confidence. Does receiving the Social
Security Statement have a stronger impact among
highly educated than less-educated individuals, as
would occur if highly educated individuals are
especially apt to pay attention to the Statement and
learn from it? We ask a similar question about those
who are more motivated and have higher incomes.
Are they more inclined to learn the new information
and then take greater advantage of it?
Individual Traits and Information
Distribution
Table 2 and Figure 2 show that memory of a personal
Statement from SSA is largely the product of actually
having been mailed one. The relationship between
‘‘Statement Mailed’’ and ‘‘Statement Received’’ is
statistically significant and very strong (b 5 .65).
This means that individuals sent the Statement by
SSA are highly likely to report they received it,
though there is some inevitable slippage owing, for
instance, to such things as moving, discarding the
envelope before opening it, being too busy to read it,
and imperfect recollection. By contrast, income,
education, and personal importance have substantially weaker influences on the respondents’ recollection of receiving the Statement (b 5 .09, .08, and
.12, respectively). Race and gender have no significant
relationship with ‘‘Statement Received.’’
The Impacts of Individual Traits on Knowledge
and Confidence . The influence of individual traits
on Knowledge and Confidence generally parallels the
previous analyses in Figure 1 and Table 1 that did
not include ‘‘Statement Received.’’ With the exception of gender, the variables for social location,
cognitive capacity, and personal importance continue to exert the positive effects on Knowledge
found for ‘‘Statement Mailed’’ (Model 1). In terms
of direct effect on Confidence, race, gender, and
personal importance remain as the only individual
traits that are statistically significant, while education
continues to improve knowledge without directly
raising confidence.
The Impact of Information on Knowledge
Adding ‘‘Statement Received’’ in Model 2 produces a
statistically significant direct path from government
405
information distribution to Knowledge (see Figure 2).
Specifically, ‘‘Statement Received’’ has a positive direct
effect on Knowledge (b 5 .18; p , .05 [Table 2,
‘‘Direct Effects’’ Panel, Column 5]). Indeed, adding
‘‘Statement Received’’ generally produced stronger
results. As Table 2 shows, the total effect of ‘‘Statement
Received’’ on Knowledge is stronger than for ‘‘Statement Mailed’’: b 5 .17 p , .05. This implies that
although sending the statement has a small but not
statistically significant impact on boosting knowledge, actually receiving the Statement improves
knowledge even more and provides additional evidence of the cognitive impact of receiving and
absorbing SSA’s information about retirement
benefits (Gilens 2001).
Impact of Information on Confidence
One of the most important results in Figure 2 and
Table 2 is that SSA’s distribution of information
exerts an indirect impact on Confidence through
Knowledge. The inclusion of both Statement Mailed
and Statement Received clarifies the effects of the
cognitive processing of information. Specifically,
receiving their Social Security Statements helps individuals gain new knowledge about Social Security
and this increased knowledge then generates more
confidence in the viability of Social Security (b 5 .35)
(Table 2, ‘‘Total Effects’’ Panel, Column 6). It seems,
then, that actual receipt of the Statement indirectly
makes a difference in increasing the confidence of
Americans by improving their understanding of the
program.
Interactions of Individual Traits and
Statement Receipt on Knowledge, and
Confidence
Analyzing the interactions of new information and
specific individual traits is critical for sorting out
whether the impact of the Social Security statement
reported above is largely limited to advantaged
groups. None of the substantively important statistical interactions with Statement Mailed or Received
reach conventional levels of statistical significance.
For instance, Table 2 shows that the interaction of
Statement Receipt and education produces a positive
(but unreliable) effect on Knowledge and an only
marginal effect on Confidence at the .10 level.
Statistical interactions between Statement Receipt
and income and personal importance are also not
statistically significant.
Direct, Indirect and Total Effects of the Variables for Model 2
Independent
variables
b (std. err)
Educ.
* Statement Rec.
b
b (std. err)
.06 (.03)*** .09 2.01 (.03)
.07 (.06)
.07
.04 (.05)
.03 (.04)
.03 2.03 (.04)
b
b (std. err)
2.02 2.18 (.06)**
.03 2.16 (.09)
2.02
.04 (.06)
.09 (.05)**
.08 226 (06)*** 2.18
.13 (.06)**
.12 2.08 (.05)
.65 (.04)*** .65 2.13 (.10)
.15 (.10)
Income *Statement
Rec
.01 (.07)
2.06 2.04 (.08)
b
Pers imp
* Stmt Rec.
b (std. err)
Knowledge
b
b (std. err)
Confidence
b
b (std. err)
b
2.14
.01 (.02)
2.08 2.06 (.04)
.02
.00 (.03)
.02
2.06
.00
.03 (.01)**
.15 (.03)***
.02 (.02)
.13
.01 (.04)
.01
.38 2.28 (.10)** 2.20
.05
.19 (.05)***
.14
.01 2.04 (.03)
.01
.14 (.02)***
.31 2.05 (.07)
2.02 2.25 (.08)** 2.24
.14 (.03)***
.33
2.10 2.27 (.16)
2.14 2.09 (.08)
.12
.41 (.15)***
.21
.01 (.07)
2.09 2.01 (.03)
.01
.07 (.03)*
.01 (.01)
2.01 (.01)
.01 (.02)
.57 (.08)***
2.02 2.04 (.10)
.18
.10 (.10)
.05
2.07
.01
.06 (.04)
.03 (.02)
.08 (.05)
2.03
.36
2.03
.07
.06
.04
.05
1.27 (.30)***
.35
.01 (.01)
.01 (.01)
.00 (.01)
.01
.01
.00
.03 (.02)
.03 (.03)
.01 (.02)
.02
.01
.01
.00 (.00)
.00 (.01)
.00 (.00)
.00
.00
.00
.01 (.00)
.01 (.00)
.00 (.00)
.03
.02
.00
.05 (.02)**
.20 (.06)***
.03 (.02)
.06
.14
.02
.01 (.01)
.01
.04 (.02)
.02
.00 (.01)
.00
.00 (.01)
.01
.17 (.05)***
.11
.02 (.01)
.01
.05 (.03)
.02
.00 (.01)
.00
.01 (.01)
.02
.18 (.05)***
.12
.10 (.06)
.08
.26 (.10)**
.14
.01 (.05)
.01
.05 (.02)*
.00 (.00)
.11 (.07)
.11 (.04)*
.08
.08
.12
2.01
.02 (.01)
2.02 (.01)
.02 (.02)
.02
2.03
.01
fay lomax cook, lawrence r. jacobs and dukhong kim
Direct Effects
A. Social Location
income
race (white 5 l, nonwhite 5 0)
gender (male5l, female50)
B. Cognitive Capacity
education
C. Motivation
personal importance
D. Information distribution
statement Mailed
statement Received
E. Interaction
educ.* statement received
income * statement received
personal imp. * statement received
F. Information
knowledge
Indirect Effects
A. Social Location
income
race (white 5 l, nonwhite 5 0)
gender (male 5 l, female 5 0)
B. Cognitive Capacity
education
C. Motivation
personal importance
D. Information distribution
statement Mailed
statement Received
E. Interaction
educ.* statement received
income * statement received
personal imp. * statement received
Statement
Rec.
406
T ABLE 2
Independent
variables
Total Effects
A. Social Location
income
race (white 5 l, nonwhite 5 0)
gender (male 5 l, female 5 0)
B. Cognitive Capacity
education
C. Motivation
personal importance
D. Information distribution
statement Mailed
statement Received
E. Interaction
educ.* statement received
income * statement received
personal imp. * statement received
F. Information
knowledge
Statement
Rec.
b (std. err)
Educ.
* Statement Rec.
b
b (std. err)
b
.06 (.03)*
.07 (.06)
.03 (.04)
.09 2.01 (.03)
.07
.05 (.05)
.03 2.03 (.04)
.09 (.04)*
.08 225 (06)*** 2.17
.13 (.05)*
.12 2.06 (.05)
.65 (.04)*** .65 2.03 (.05)
.15 (.10)
Income *Statement
Rec
b (std. err)
2.01 2.16 (.05)**
.04 2.13 (.08)
2.02
.05 (.06)
2.04
b
Pers imp
* Stmt Rec.
b (std. err)
Knowledge
b
b (std. err)
Confidence
b
b (std. err)
b
2.12
.02 (.02)
2.07 2.06 (.04)
.03
.00 (.03)
.02
2.06
.00
.04 (.01)***
.15 (.03)***
.02 (.02)
.15
.07 (.03)
.07
.40 2.08 (.07)
2.06
.06
.22 (.05)***
.16
.03 (.06)
.01 2.04 (.03)
2.04
.14 (.02)***
.31
.12 (.05)*
.07
.01 (.08)
.00 2.25 (.08)** 2.24
.15 (.02)***
.35
.76 (.06)***
.48
.00 2.08 (.05)
.21
.01 (.07)
.04 (.02)
.07 (.03)*
.10
.17
.06 (.06)
.21 (.09)*
.05
.15
.05
2.07
.01
.08 (.03)*
.01 (.02)
.08 (.05)
.07
.01
.06
1.27 (30)**
.35
2.02 2.01 (.09)
.12
.41 (.15)**
2.09
.01
.01 (.01)
2.01 (.01)
.01 (.02)
trusting what you know
TABLE 2 (Continued)
***: p , 5.001:**:p , 5 .01*: p , 5 .05
The unstandardized (b) and standardized (b) coefficients are presented. The estimation has been conducted by using LISREL 8.5. df 5 275; S.B Chi-square 5 426.39; AGFI 5 .98;
RMSEA 5 .017; SRMR 5 .056
407
408
fay lomax cook, lawrence r. jacobs and dukhong kim
F IGURE 2 The Impact of Both Mailing and Receiving the Social Security Statement on Knowledge and
Confidence
But most impressive is the continuing independent
direct impact of Statement Receipt on Knowledge and
its indirect effects on Confidence through Knowledge
after the introduction of interactions of Statement
Receipt and individual traits. These notable results
imply that the effects of mailing and sending the Social
Security Statement had general effects on Americans
and were not limited to certain subgroups.
Discussion and Conclusion
Our analysis has implications for research on confidence and for discussions on how to improve civic
life in America. It confirms the importance of shifting
research on political trust and confidence away from
global objects of evaluation like ‘‘the government’’
and towards judgments about specific institutions
and their performance (Gilens 2001; Levi and Stoker
2000). Three contributions merit attention.
First, our findings modify earlier research on the
reasoning capacity of the mass public. Previous
research largely accepted that the public’s level of
information was minimal and instead emphasized the
rational processes that citizens use to process the
limited information they do possess (Bartels 1996,
197; Page and Shapiro 1992; Popkin 1991). Our
results raise questions, however, about the immutability of minimal levels of citizen information and
offer qualified evidence that policy information can
be boosted when the public is provided with clear,
useful, and personally relevant factual information
from credible sources. Borrowing on V.O. Key’s
famous aphorism, the public’s level of policy knowledge echoes the quality and quantity of information
with which they are provided. A related implication
is to underscore the feedback effects of specific government programs (Campbell 2003; Mettler 2002;
Mettler and Soss 2003).
Second, our findings show that information
distribution can improve confidence. In line with
previous studies on confidence, we find that social
status, cognitive ability, and self motivation enhance
citizens’ confidence. However, unlike previous
trusting what you know
pessimistic studies about the relationship between
knowledge and confidence (e.g., Delli Carpini and
Keeter 1996; Hibbing and Theiss-Morse 1995, 2002;
Kimball and Patterson 1997), we found that sending
out objective information can boost citizens’ knowledge about Social Security programs across individuals with disparate traits and in turn improve their
confidence in the program. This gives credence to Bok
and others’ argument that citizens’ lack of knowledge
contributes to the lower level of confidence in government in general and reveals a concrete direction
through which to enhance citizen confidence in
government.
Third, our study illustrates an approach to studying citizen trust in government that moves away from
focusing on a global object of evaluation to examining a specific object of evaluation. Asking citizens
whether or not they trust ‘‘the government in
Washington’’ depends on their abstract or impressionistic judgments of government. By contrast,
studying citizen evaluation on a specific government
institution makes it possible to investigate the effect
of knowledge about concrete programs on the evaluation of that institution’s ability to deliver on its
mission (Page and Jacobs 2009). Although we have
not addressed the question how domain-specific
evaluation is connected to global evaluation, we think
such an examination would be a useful next step.
Findings that support the information-enhancement
account have practical implications for American
civic life. Evidence that the public’s confidence in
government may, in part, be related to its knowledge
underscores the value of providing fact-rich, clear,
and personally relevant information (Bok 1997;
Jacobs, Cook, and Delli Carpini 2009). Our results
provide conditional support for government initiatives like SSA’s Statements to increase knowledge and
confidence toward government programs. Although
our analysis shows the effects of social location, cognitive capacity, and, especially, personal motivation,
it also demonstrates that government distribution of
factual information can have independent effects on
confidence.
A particular challenge for government institutions is to encourage citizens to read and retain the
information sent to them. As our findings suggest,
sending out well-presented information has a direct
impact on confidence but this effect is stronger when
citizens actually read the materials and remember
them.
Foundations, schools, and other organizations
have fueled a burgeoning movement to improve civic
engagement and boost policy knowledge and con-
409
fidence. Less explored has been how government
itself can help. Decisions by government officials
about the amount, kind, and delivery vehicle for
the distribution of information may have a measurable impact on public knowledge and confidence in
government. Major government programs should
carefully review the nature of the information they
distribute because it has consequential (even if
modest) impacts on citizens. Although an Athenian
conclave of learned citizenry is not attainable, government institutions may be able to measurably
improve the level of policy information and boost
the public’s evaluation of its programs.
Acknowledgments
We gratefully acknowledge the insightful comments
and helpful assistance of Dennis Chong, James
Druckman, Jon Krosnik, Jeff Manza, David Mechanic,
Joanne Miller, Thomas D. Cook, Steve West, and Will
Shadish. We also thank Ellen Whittingham on expert
help with formatting and typing the figures. Authors’
names are listed in alphabetical order.
Appendix
Data
This survey was supported by the Social Security
Administration as an effort to monitor what the
public knows about Social Security. The Gallup
Organization conducted the survey for the Social
Security Administration first between October and
November 1998 and second between November 1999
and January 2000. For the analysis in this paper, the
second survey is used. The total number of respondents in the second survey was 4,020 adults. Four
hundred adult respondents were randomly sampled
in 10 major regions (Boston, New York, Philadelphia,
Atlanta, Chicago, Dallas, Kansas City, Denver, San
Francisco, and Seattle). To represent the nation at
large, Gallup then applied weights. We conducted our
analyses with and without weights. Finding no differences in the results, we report our finding without the
use of weights.
Because the focus of this paper is on the effect of the
Social Security Statements, we limited our analysis to
those respondents targeted for the statements (i.e.,
those who are not already receiving Social Security).
Therefore, we excluded respondents aged under 25,
410
fay lomax cook, lawrence r. jacobs and dukhong kim
aged 65 and over, and any respondents under 65 who
are getting benefits. The resulting N was 2458.
The statistical packages used in this analysis is
LISREL 8.5.
Dependent Variable
Confidence in Social Security. Q4: ‘‘How confident are you that Social Security retirement benefits
will be there for you when you retire?’’ (Not
confident at all, Only a little confident, Somewhat
confident, Very confident). (Min 5 1 Max 5 4
Mean 5 2.20 Std. Dev 5 1.01 N 5 2408)
Independent Variables
Knowledge. Q2, Q3(ABDEF), Q5,6,7,9,10,14(B,C)
Q2: What types of benefits do you think the
Social Security taxes that come out of your pay check
are for ? [This is an open-ended question which
allows the respondent seven responses. The score for
these seven responses were calculated by adding the
number of correct answers. Thus each correct response was treated as an individual question. The
correct answers are 6 (disability benefits), 10 (retirement benefits), and 12 (survivor benefits).]
Q3A: Social Security provides retirement benefits
(agree or disagree).
Q3B: Social Security provides benefits to the
families of workers who die (agree or disagree).
Q3D: Social Security pays benefits to workers
who become disabled (agree or disagree).
Q3E: Social Security benefits play a major role in
keeping many senior citizens out of poverty (agree or
disagree).
Q3F: Social Security is paid for by a tax placed on
both workers and employers (agree or disagree).
Q5: What do you think is the youngest age
someone can retire today, and start receiving FULL
Social Security retirement benefits? If you don’t know
just say so (open ended question).
Q6: Is the youngest age you can retire and collect
FULL Social Security retirement benefits fixed or will
it rise in the future?
Q7: Can a person retire early and still receive
some Social Security retirement benefits?
Q9: Do all people who receive Social Security
retirement benefits receive the same amount, or does
it depends on how much people earned when they
were working?
Q10: Were Social Security retirement benefits, by
themselves, designed to provide enough money for
retired people to live on?
Q14 B: People on Social Security are living
longer, so they cost the program more money.
Q14 C: The percentage of older Americans will
about double between now and the year 2032.
Cronbach Alpha is .61 for these items.
(Min 5 0 Max 5 16 Mean 5 10.199 Std. Dv 5
2.553 N 5 2458)
Personal Importance. For this variable, two
items (Q D3, and D5) were added.
D3: Is anyone else in your household currently
receiving any Social Security benefits?
D5: What is your age? Age is recoded by 1 5 56
or over and 0 5 under age 56.
(Min 5 0 Max 5 2 Mean 5 .2297 Std. Dv 5 .4771
N 5 2451)
Statement Received. Q24: Have you received a
written statement (the Social Security Statement)
from the Social Security Administration in the last
year that shows how much you have contributed to
Social Security and how much you can expect to
receive in benefits?
(Min 5 0 Max 5 1 Mean 5 .2883 Std. Dv 5 .4531
N 5 2397)
Statement Mailed. QD11a: In what month were
you born? This variable has been modified as a
dichotomous variable. Respondents who were born
in January and February were coded as 1 and those
who were born in other months 0. But the respondents who were born in March were excluded in order
to make the variable cleaner because people born in
March were in the ambiguous situation with some
having received the statement and others not having
receiving it.
(Min 5 0 Max 5 1 Mean 5 .154 Std. Dv 5 .361
N 5 2269)
Education. Originally it ranged from 1 5 less
than high school graduate to 6 5 postgraduate work/
degree. People who chose ‘‘trade/technical/vocational
training’’ were assigned to ‘‘some college’’ category.
Thus, the variable ranges from 1 to 5.
(Min 5 1 Max 5 5 Mean 5 3.136 Std. Dv 5 1.14
N 5 2452)
Race. This variable was coded 1 for white and 0
for nonwhite.
(Minimum 5 0
Maximum 5 1
Mean 5 .8855
Std. Dv 5 .3185 N 5 2245)
Income. It ranges from 15 Less than $20,000 to
65$100,000 or more.
(Minimum 5 1
Maximum 5 6
Mean 5 3.366
Std. Dv 5 1.549 N 5 2222)
trusting what you know
Gender. Male was coded as 1 and female 0.
(Minimum 5 0
Maximum 5 1
Mean 5 .4365
Std. Dv 5 .4961 N 5 2458)
Manuscript submitted 14 January 2009
Manuscript accepted for publication 9 September 2009
References
Abramson, Paul. 1983. Political Attitudes in America. San Francisco:
Freeman.
Aiken Leona, S., and Stephen G. West. 1991. Multiple Regression:
Testing and Interpreting Interactions. Newbery Park, CA: Sage
Publications.
Barber, Benjamin. 1983. The Logic and Limits of Trust. New
Brunswick, NJ: Rutgers University Press.
Bartels, Larry M. 1996. ‘‘Uninformed Votes: Information Effects
in Presidential Elections.’’ American Journal of Political Science
40 (2): 194–230.
Bennett, Stephen. 1995. ‘‘Comparing Americans’ Political Information in 1988 and 1992.’’ Journal of Politics 57 (May):
521–32.
Bentler, Peter M., and Paul Dudgeon. 1996. ‘‘Covariance Structure Analysis: Statistical Practice, Theory, and Directions.’’
Annual Review of Psychology 47: 563–92.
Blendon, Robert, John Benson, Richard Morin, Drew Altman,
Mollyann Brodie, Mario Brossard, and Matt James. 1997.
‘‘Changing Attitudes in America.’’ In Why People Don’t Trust
Government, eds. Joseph Nye, Jr., Philip Zelikow, and David
King. Cambridge, MA: Harvard University Press, 205–16.
Bok, Derek. 1997. ‘‘Measuring the Performance of Government.’’
In Why People Don’t Trust Government, eds. Joseph Nye, Jr.,
Philip Zelikow, and David King. Cambridge, MA: Harvard
University Press, 55–75.
Bollen, Kenneth A. 1989. Structural Equations with Latent
Variables. New York: John Wiley and Sons.
Brehm, John, and Wendy Rahn. 1997. ‘‘Individual-Level Evidence for the Causes and Consequences of Social Capital.’’
American Journal of Political Science 41 (3): 999–1023.
Byrne, Barbara M. 1998. Structural Equation Modeling with
LISREL, PRELIS, and SIMPLIS. Mahwah, NJ: Lawrence
Erlbaum Associates.
Campbell, Andrea Louise. 2003. How Policies Make Citizens:
Senior Political Activism and the American Welfare State.
Princeton, NJ: Princeton University Press.
Campbell, Angus, Philip Converse, Warren Miller, and Donald
Stokes. 1960. The American Voter. Midway Reprint (1980).
Chicago: University of Chicago Press.
Chanley, Virginia, Thomas Rudolph, and Wendy Rahn. 2000.
‘‘The Origins and Consequences of Public Trust in Government,’’ Public Opinion Quarterly 64 (3): 239–56.
Chong, Dennis. 2000. Rational Lives: Norms and Values in Politics
and Society. Chicago: University of Chicago Press.
Citrin, Jack. 1974. ‘‘Comment: The Political Relevance of Trust in
Government.’’ American Political Science Review 68 (September):
973–88.
Converse, Philip E. 1964. ‘‘The Nature of Belief Systems in Mass
Publics.’’ In Ideology and Discontent, ed. David Apter.
New York: Free Press, 206–64.
411
Cook, Fay Lomax, Jason Barabas, and Benjamin I. Page. 2002.
‘‘Invoking Public Opinion: Policy Elites and Social Security.’’
Public Opinion Quarterly 66 (2): 235–64.
Cook, Fay Lomax, and Lawrence R. Jacobs. 2000. ‘‘Assessing
Assumptions about Attitudes toward Social Security: Popular
Claims Meet Hard Data. In The Future of Social Insurance, eds.
Peter Edelman, Dallas L. Salisbury, and Pamela Larson.
Washington, DC: Brookings Institution Press, 82–110.
Craig, Stephen. 1996. ‘‘Change and the American Electorate.’’ In
Broken Contract: Changing Relationships between Americans
and Their Government, ed. S. Craig. Boulder, CO: Westview,
1–20.
Delli Carpini, Michael X., and Scott Keeter. 1996. What Americans
Know about Politics and Why It Matters. New Haven, CT: Yale
University Press.
Dunn, Jennifer. 1999. ‘‘The Republican Response to President
Clinton’s State of the Union Address.’’ January 20: http://
www.thewashingtonpost.com/wp-srv/politics/soecuak/states/
docs/gop99.htm.
Flynn, James, William Burns, C.K. Mertz, and Paul Slovic. 1992.
‘‘Trust as a Determinant of Opposition to a High-Level
Radioactive Waste Repository: Analysis of a Structural
Model.’’ Risk Analysis 12 (3): 417–29.
Gilens, Martin. 2001. ‘‘Political Ignorance and Collective Policy
Preferences.’’ American Political Science Review 95 (June):
379–96.
Goldsteen, Raymond, Karen Goldsteen, and John Schorr. 1992.
‘‘Trust and Its Relationship to Psychological Distress:
The Case of Three Mile Island.’’ Political Psychology 13 (4):
693–707.
Gordon, Stacy, and Gary Segura. 1997. ‘‘Cross-National Variation in the Political Sophistication of Individuals: Capability
or Choice?’’ Journal of Politics 59 (February): 126–47.
Green, Donald Philip. 1998. ‘‘On the Dimensionality of Public
Sentiment toward Partisan and Ideological Groups.’’
American Journal of Political Science 32 (August): 758–80.
Hetherington, Marc. 1998. ‘‘The Political Relevance of Political
Trust.’’ American Political Science Review 92 (December):
791–808.
Hetherington, Marc. 1999. ‘‘The Effect of Political Trust on the
Presidential Vote, 1968--96.’’ American Political Science Review
93 (June): 311–26.
Hetherington, Marc, and John Nugent. 1998. ‘‘Explaining Public
Support for Devolution: The Role of Political Trust.’’ Presented at the Hendricks Symposium on Public Dissatisfaction
with Government, University of Nebraska, Lincoln.
Hibbing, John, and Elizabeth Theiss-Morse. 1995. Congress as
Public Enemy: Public Attitudes toward American Political
Institutions. New York: Cambridge University Press.
Hibbing, John, and Elizabeth Theiss-Morse. 2002. Stealth Democracy: American’s Beliefs about How Government Should
Work. New York: Cambridge University Press.
Hu, Li tze, and Peter M. Bentler. 1999. ‘‘Cutoff Criteria for Fit
Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives.’’ Structural Equation Modeling
6 (1): 1–55.
Jacobs, Lawrence R., and Robert Y. Shapiro. 1998. ‘‘Myths and
Misunderstandings about Public Opinion toward Social
Security.’’ In Framing the Social Security Debate: Values,
Politics, and Economics, eds. R. Douglas Arnold, Michael J.
Graetz, and Alicia H. Munnell. Washington, DC: Brookings
Institution, 355–88.
412
fay lomax cook, lawrence r. jacobs and dukhong kim
Jacobs, Lawrence R., Fay Lomax Cook, and Michael Delli
Carpini. 2009. Talking Together: Public Deliberation and
Political Participation in America. Chicago: University of
Chicago Press.
Joreskog Karl, and Dag Sorbom. 1996. LISREL 8: User’s Reference
Guide. Chicago: Scientific Software International.
Joreskog Karl, G., and Fan Yang. 1996. ‘‘Nonlinear Structural
Equation Models: The Kenny-Judd Model with Interaction
Model.’’ In Advanced Structural Equation Modeling: Issues and
Techniques, eds. George A. Marcoulides, and Randall E.
Schumacker. Mahwah, NJ: Lawrence Erlbaum Associates,
57–88.
Kahn, Kim, and Patrick Kenney. 1997. ‘‘A Model of Candidate
Evaluation in Senate Elections: The Impact of Campaign
Intensity.’’ Journal of Politics 59 (November): 1173–1205.
Kimball, David, and Samuel Patterson. 1997. ‘‘Living Up to
Expectations: Public Attitudes toward Congress.’’ Journal of
Politics 59 (3): 701–28.
King, David C. 1997. ‘‘The Polarization of American Parties and
Mistrust of Government.’’ In Why People Don’t Trust Government, eds. Joseph Nye, Jr., Philip Zelikow, and David King.
Cambridge, MA: Harvard University Press, 155–78.
Langer, Gary. 2002. ‘‘Trust in Government.’’ Public Perspective
July/August: 7–10.
Lieberman, Robert. 1998. Shifting the Color Line: Race and the
American Welfare State. Cambridge, MA: Harvard University
Press.
Levi, Margaret, and Laura Stoker. 2000. ‘‘Political Trust and
Trustworthiness.’’ Annual Review of Political Science 3: 475–507.
McAllister, Ian. 1999. ‘‘The Economic Performance of Governments.’’ In Critical Citizens: Global Support for Democratic
Government, ed. Pippa Norris. New York: Oxford University
Press, 188–203.
McClosky, Herbert, and John Zaller. 1984. The American Ethos:
Public Attitudes toward Capitalism and Democracy.
Cambridge, MA: Harvard University Press.
Mettler, Suzanne. 2002. ‘‘Bringing the State Back in to Civic
Engagement: Policy Feedback Effects of the G.I. Bill for World
War II Veterans.’’ American Political Science Review 96 (June):
351–65.
Mettler, Suzanne, and Joe Soss. 2003. ‘‘Beyond Representation:
Policy Feedback and the Political Roots of Citizenship.’’
Presented at the annual meeting of the Midwestern Political
Science Association.
Miller, Arthur. 1974a. ‘‘Political Issues and Trust in Government,
1964--70.’’ American Political Science Review 68 (September):
951–72.
Miller, Arthur. 1974b. ‘‘Rejoinder to Comment by Jack Citrin:
Political Discontent or Ritualism.’’ American Political Science
Review 68 (September): 989–1001.
Nadeau, Richard, Richard Niemi, and Timothy Amato. 1995.
‘‘Emotions, Issue Importance, and Political Learning.’’ American Journal of Political Science 39 (August): 558–74.
Nie, Norman H, Jane Junn, and Kenneth Stehlik-Barry. 1996.
Education and Democratic Citizenship in America. Chicago:
University of Chicago Press.
Norris, Pippa (ed.). 1999. Critical Citizens: Global Support for
Democratic Government. New York: Oxford University Press.
Nye, Joseph, Jr., Philip Zelikow, and David King. 1997. Why
People Don’t Trust Government. Cambridge, MA: Harvard
University Press.
Nye, Joseph, Jr., and Philip Zelikow. 1997. ‘‘Conclusion: Reflections, Conjectures, and Puzzles.’’ In Why People Don’t Trust
Government, eds. Joseph Nye, Jr., Philip Zelikow, and David
King. Cambridge, MA: Harvard University Press, 253–81.
Orren, Gary. 1997. ‘‘Fall from Grace: The Public’s Loss of Faith in
Government.’’ In Why People Don’t Trust Government, eds.
Joseph Nye, Jr., Philip Zelikow, and David King. Cambridge,
MA: Harvard University Press, 77–107.
Page, Benjamin I., and Robert Shapiro. 1992. The Rational Public.
Chicago: University of Chicago Press.
Page, Benjamin I., and Lawrence I. Jacobs. 2009. Class War: What
Americans Really Think About Economic Inequality. Chicago:
University of Chicago Press.
Pedhazur, Elazar J. 1982. 2nd ed. Multiple Regression in Behavioral Research: Explanation and Prediction. New York: Harcourt Brace College Publishers.
President’s Commission to Strengthen Social Security. 2001.
Strengthening Social Security and Creating Personal Wealth
for All Americans. Washington, DC: GPO.
Popkin, Samuel L. 1991. The Reasoning Voter: Communication
and Persuasion in Presidential Campaigns. Chicago: University
of Chicago Press.
Shadish, William R., Thomas D. Cook, and Donald T. Campbell.
2002. Experimental and Quasi-experimental Designs for Generalized Causal Inference. New York: Houghton Mifflin.
Schumpeter, Joseph A. 1950. Capitalism, Socialism, and Democracy. New York: Harper.
Shapiro, S. P. 1987. ‘‘The Social Control of Impersonal Trust.’’
American Journal of Sociology 93 (3): 623–58.
Verba, Sidney, Nancy Burns, and Kay Lehman Schlozman. 1997.
‘‘Knowing and Caring about Politics: Gender and Political
Engagement.’’ Journal of Politics 59 (November): 1051–72.
Zaller, John. 1992. The Nature and Origins of Mass Opinion.
New York: Cambridge University Press.
Fay Lomax Cook is Director of the Institute for
Policy Research and Professor of Human Development and Social Policy and of Political Science at
Northwestern University, Evanston, IL 60208-4100.
Lawrence R. Jacobs is Walter F. and Joan
Mondale Chair for Political Studies and Director of
the Center for the Study of Politics and Governance
at the University of Minnesota, Minneapolis, MN
55455.
Dukhong Kim is Assistant Professor in the
Department of Political Science, Florida Atlantic
University, Boca Raton, FL 33431.